Estimating Stop-Loss Clusters to Anticipate Breakout Activity

Summary

This indicator estimates where stop orders may cluster around swing highs and lows, then displays active and previously violated clusters as potential breakout areas. Its absorption-extremes model identifies price swings using an ATR-based reversal threshold and uses lower-timeframe volume information to estimate the size and location of stop clusters. The script can highlight recent clusters, draw projected paths, vary color intensity with estimated size, and compare active versus removed buy- and sell-stop levels.

A second, time-scaled volatility model organizes levels using volatility and volume data at a selected timeframe, with options to show historical triggers and cluster size. Alerts can mark large buy- or sell-stop cluster events, and a ratio meter summarizes relative cluster activity. These are estimates inferred from chart data, not direct observations of an order book or verified stop orders. The supplied script excerpt describes visualization and alert logic but offers no validation, trading results, or evidence that a cluster predicts a breakout; interpretation and performance therefore remain uncertain.

Key ideas

• The indicator infers possible stop concentrations around detected swing highs and lows.
• Its absorption-extremes model combines ATR-based swing detection with lower-timeframe volume information.
• Active and violated clusters can be displayed separately for buy-side and sell-side levels.
• A time-scaled volatility model offers another way to map potential clusters and breakout triggers.
• The inferred levels are estimates, and the document provides no performance validation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.